Validation and stability of cox models to predict survival after coronary angioplasty
نویسندگان
چکیده
منابع مشابه
Investigation factors affecting the first recurrence of coronary artery disease in patients undergone angioplasty using cox survival model
Background: The incidence of restenosis in patients suffering from coronary artery disease after undergoing angioplasty is of paramount importance. Accordingly, this study aimed to investigate factors affecting the time of the first incidence of restenosis in patients undergone angioplasty in the city of Zanjan, Iran. Methods: This retrospective cohort study was conducted on 421 patie...
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Comparison of Artificial Neural Networks and Cox Regression Models in Prediction of Kidney Transplant Survival
Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...
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Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...
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Introduction: Ischemic preconditioning mediated by potassium channels is a physiological protective mechanism, . It is hypothesized that Nicorandil, which is a potassium channel activator, could protect the heart via preconditioning. Materials and Methods:This clinical trial was conducted on 162 patients undergoing percutaneous coronary intervention (PCI) in Quem hospital, from Jan2013 to Jan 2...
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ژورنال
عنوان ژورنال: Journal of the American College of Cardiology
سال: 1996
ISSN: 0735-1097
DOI: 10.1016/s0735-1097(96)81629-9